...
首页> 外文期刊>Royal Society Open Science >Prediction limits of mobile phone activity modelling
【24h】

Prediction limits of mobile phone activity modelling

机译:手机活动建模的预测极限

获取原文
   

获取外文期刊封面封底 >>

       

摘要

Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.
机译:由于它们的广泛使用,移动设备已成为人类行为的主要传感器之一,并且留下的数字迹线可以用作研究城市环境的代理。因此,探索手机活动的时空模式的本质可能是迈向了解人类活动的全部方面的关键一步。使用大伦敦地区10个月的手机记录在时空上的解析,我们研究了人类电信活动在城市规模上的规律性。我们评估了将活动时间表分解为典型模式和残差模式的几种方法,其中考虑了强烈的周期性和季节性因素。我们在各种空间尺度上进行了分析,结果表明,当我们查看较大空间单位中的聚集活动并具有更多活动时,规律性会增加。我们检查了残差的统计特性,并表明可以用噪声和特定离群值来解释。此外,我们还会查看与总体趋势的偏差来源,基于对城市结构和景点的了解,我们认为这是可以解释的。我们举例说明一些离群值如何与外部因素(例如特定的社会事件)相关联。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号